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A Damaged-Informed Lung Ventilator Model for Ventilator Waveforms

ABSTRACT: Motivated by a desire to understand pulmonary physiology, scientists have developed physiological lung models of varying complexity. However, pathophysiology and interactions between human lungs and ventilators, e.g., ventilator-induced lung injury (VILI), present challenges for modeling efforts. This is because the real-world pressure and volume signals may be too complex for simple models to capture, and while complex models tend not to be estimable with clinical data, limiting clinical utility. To address this gap, in this manuscript we developed a new damaged-informed lung ventilator (DILV) model. This approach relies on mathematizing ventilator pressure and volume waveforms, including lung physiology, mechanical ventilation, and their interaction. The model begins with nominal waveforms and adds limited, clinically relevant, hypothesis-driven features to the waveform corresponding to pulmonary pathophysiology, patient-ventilator interaction, and ventilator settings. The DILV model parameters uniquely and reliably recapitulate these features while having enough flexibility to reproduce commonly observed variability in clinical (human) and laboratory (mouse) waveform data. We evaluate the proof-in-principle capabilities of our modeling approach by estimating 399 breaths collected for differently damaged lungs for tightly controlled measurements in mice and uncontrolled human intensive care unit data in the absence and presence of ventilator dyssynchrony. The cumulative value of mean squares error for the DILV model is, on average, ≈12 times less than the single compartment lung model for all the waveforms considered. Moreover, changes in the estimated parameters correctly correlate with known measures of lung physiology, including lung compliance as a baseline evaluation. Our long-term goal is to use the DILV model for clinical monitoring and research studies by providing high fidelity estimates of lung state and sources of VILI with an end goal of improving management of VILI and acute respiratory distress syndrome.

SUBMITTER: Agrawal D

PROVIDER: S-EPMC8517122 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundFor patients with acute respiratory distress syndrome, a ventilator is essential to supply oxygen to tissues, but it may also cause lung damage. In this study, we investigated the role of NOX4 using NOX4 knockout (KO) mice and NOX4 inhibitors in a ventilator-induced lung injury (VILI) model.MethodsWild-type (WT) male C57BL/6J mice and NOX4 knockout (KO) male mice were divided into five groups: (1) control group; (2) high tidal ventilation (HTV) group: WT mice + HTV ± DMSO; (3) NOX4 KO group; (4) NOX4 KO with HTV group; (5) NOX4 inhibitor group: WT mice + HTV + NOX4 inhibitor. In the VILI model, the supine position was maintained at 24 mL/kg volume, 0 cm H2O PEEP, 100/min respiratory rate, and 0.21 inspired oxygen fraction. In the NOX4 inhibitor group, 50 μL anti-GKT 137831 inhibitor was injected intraperitoneally, 2 h after ventilator use. After 5 h of HTV, mice in the ventilator group were euthanized, and their lung tissues were obtained for further analysis. In addition, the relationship between EphA2 (which is related to lung injury) and NOX4 was investigated using EphA2 KO mice, and NOX4 and EphA2 levels in the bronchoalveolar lavage fluid (BALF) of 38 patients with pneumonia were examined.ResultsCell counts from BALFs were significantly lower in the NOX4 KO with HTV group (p < 0.01) and EphA2 KO with HTV group (p < 0.001) compared to that in the HTV group. In the NOX4 inhibitor group, cell counts and protein concentrations from BALF were significantly lower than those in the HTV group (both, p < 0.001). In the NOX4 KO group and the NOX4 inhibitor group, EphA2 levels were significantly lower than those in the HTV group (p < 0.001). In patients with respiratory disease, NOX4 and EphA2 levels were significantly higher in patients with pneumonia and patients who received ventilator treatment in the intensive care unit.ConclusionIn the VILI model with high tidal volume, NOX4 KO, EphA2 KO or monoclonal antibodies attenuated the VILI. NOX4 and EphA2 levels were significantly higher in patients with pneumonia and especially in mechanical ventilated in the ICU. Inhibition of Nox4 is a potential therapeutic target for the prevention and reduction of VILI.

Project description:BackgroundMechanical ventilation could lead to ventilator-induced lung injury (VILI), but its underlying pathogenesis remains largely unknown. In this study, we aimed to determine the genes which were highly correlated with VILI as well as their expressions and interactions by analyzing the differentially expressed genes (DEGs) between the VILI samples and controls.MethodsGSE11434 was downloaded from the gene expression omnibus (GEO) database, and DEGs were identified with GEO2R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using DAVID. Next, we used the STRING tool to construct protein-protein interaction (PPI) network of the DEGs. Then, the hub genes and related modules were identified with the Cytoscape plugins: cytoHubba and MCODE. qRT-PCR was further used to validate the results in the GSE11434 dataset. We also applied gene set enrichment analysis (GSEA) to discern the gene sets that had a significant difference between the VILI group and the control. Hub genes were also subjected to analyses by CyTargetLinker and NetworkAnalyst to predict associated miRNAs and transcription factors (TFs). Besides, we used CIBERSORT to detect the contributions of different types of immune cells in lung tissues of mice in the VILI group. By using DrugBank, small molecular compounds that could potentially interact with hub genes were identified.ResultsA total of 141 DEGs between the VILI group and the control were identified in GSE11434. Then, seven hub genes were identified and were validated by using qRT-PCR. Those seven hub genes were largely enriched in TLR and JAK-STAT signaling pathways. GSEA showed that VILI-associated genes were also enriched in NOD, antigen presentation, and chemokine pathways. We predicted the miRNAs and TFs associated with hub genes and constructed miRNA-TF-gene regulatory network. An analysis with CIBERSORT showed that the proportion of M0 macrophages and activated mast cells was higher in the VILI group than in the control. Small molecules, like nadroparin and siltuximab, could act as potential drugs for VILI.ConclusionIn sum, a number of hub genes associated with VILI were identified and could provide novel insights into the pathogenesis of VILI and potential targets for its treatment.

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A Damaged-Informed Lung Ventilator Model for Ventilator Waveforms

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